Stress/Strain Curves Extrapolated in
Function of Material Properties with
modeFRONTIER®
modeFRONTIER® can be used to extrapolate stress/
strain curves in function of material properties, saving
many material testing samples.
This feature can be achieved through RSM

formed by the decreasing local cross-sectional

(Response Surface Methods), trained by testing

area) increases until the rupture or failure point.

database.

Less ductile materials such as aluminium or brittle

During testing of a material sample, the stress–

materials like ceramics do not have a defined

strain curve is a graphical representation of

yield point, therefore the stress-strain curve would

the relationship between stress, derived from

consist mainly of elastic region, followed by the

measuring the load applied on the sample, and

failure of the material.

strain, derived from measuring the deformation

Testing of material samples are generally expensive

of the sample. The nature of the curve

and time-requiring, and to find a material with

varies from material to material.

required characteristics, it is usually necessary
repeat testing on many samples until the expected

Steel generally exhibits a very linear

material is found.

stress–strain relationship up to a well

By modeFRONTIER® and its RSM (Response

defined yield point, and the slope is

Surface Methodology) tools, from an experimental

defined as the Young’s Modulus. As

database it is now possible to predict material

deformation

stress

behaviour, such as true stress-strain curve and

increases until it reaches the ultimate

true strain failure, in function of material properties,

strength.

even if different from the database ones.

continues,

the

In addition, it is possible by a Virtual Optimisation,
Until this point the cross-sectional area decreases,

Programmes like modeFRONTIER® are most commonly used to optimise the design of systems, seeking to achieve user-defined goals
(e.g. maximising efficiency or minimising pressure drops) by varying input parameters, and by defining a computational environment in
which any CAE tool is coupled to allow a full automatic series of design runs, driven by an optimisation algorithm.
Nevertheless, modeFRONTIER® includes many post-processing and analysis tools, such as RSM (Response Surface Methodologies),
that allow to build a mathematical response of any system, starting from an available database. The RSM can then be used to extrapolate
a response in function of a variation of the input parameters, or to produce a virtual optimisation (the output responses are not computed
by a CAE tool or by an experimental test, but are obtained directly and instantly from the mathematical model), i.e. to find the combination
of input parameters that give the optimal solutions.
Example: RSM applied to Stress-Strain curves database
To show how this procedure can be applied, an experimental database of stress-strain curves, relative to 14 different material samples,
has been chosen. An Excel sheet contains data relative to 5 material physical or technological properties, that identify each different
material (Young Modulus, Age, Temp, RTW, Pitch), and the corresponding True Strain and True Stress curve data, including the True
Strain Failure data.
Fig. 2

Fig. 3

Database importing and RSM training
The Excel sheet containing material database is
imported in modeFRONTIER® through an easyto-use Data Wizard (Fig. 2), that step by step
drives the user to select which columns contain
input parameters and which ones contain output
data (True stress and Strain failure). Once the
database is imported (and a logic workflow is
automatically built), the several database curves
can be visualised (Fig. 3), and finally the RSM

Fig. 4

can be automatically trained, using also in this
case an easy-to-use RSM Wizard.
At this point, a RSM function plot can be used
to visualise a stress-strain curve in function of
any combination of input material parameters
(Fig. 4).
RSM Function Plot
By this feature, it is possible to compare
extrapolated stress-strain curves with database

ones, and even to change input parameters in the dockable slide-bar menu, to have a

Fig. 5

prediction of stress-strain curve for a material with modified property parameters (e.g.,
different Young Modulus, Age or RTW parameters).
Virtual Optimisation to find optimal material parameters
The RSM can be finally used to run a virtual optimisation, after having defined some goals
to be achieved, such as maximise Young Modulus and True Strain Failure at same time.
An optimisation algorithm (Multi-Objective-Genetic-Algorithm) obtains from the RSM the
extrapolated outputs, and proposes several material properties combinations until the goals
are achieved. In this case, the optimal material properties identify a stress-strain curve
(Fig. 5, blue line) that seems to give better performances than original database ones.